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## from Ulrike Groempings web site at prof.beuth-hochschule.de/groemping.
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## Type citation('dendextend') for how to cite the package.
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## The github page is: https://github.com/talgalili/dendextend/
##
## Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
## Or contact: <tal.galili@gmail.com>
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## To suppress this message use: suppressPackageStartupMessages(library(dendextend))
## ---------------------
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#If the package "cellrangerRkit" has not been installed, use the following lines to install it from GitHub
# install.packages("devtools")
# install.packages("roxygen2")
# library(devtools)
# library(roxygen2)
# devtools::install_github("hb-gitified/cellrangerRkit", build_vignettes = FALSE)
require(cellrangerRkit)
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## Welcome to Bioconductor
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## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.
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# Before running, change the Proj.Home variable below to the file path of the parent folder containing Notebook.Rmd.
Proj.Home = "/Users/jacobn07/Documents/GFHK99_Multiplicity"
setwd(Proj.Home)
knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE, fig.margin = TRUE)
theme_set(theme_grey())
g_legend<-function(a.gplot){
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
legend
}
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## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_DF1_0.07 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_DF1_0.07
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_DF1_0.2 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_DF1_0.2
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_DF1_0.6 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_DF1_0.6
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_DF1_1.8 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_DF1_1.8
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_MDCK_0.07 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_MDCK_0.07
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_MDCK_0.2 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_MDCK_0.2
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_MDCK_0.6 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_MDCK_0.6
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using WT_MDCK_1.8 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/WT_MDCK_1.8
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using DF1_0.02 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/DF1_0.02
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using DF1_0.07 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/DF1_0.07
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using DF1_0.2 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/DF1_0.2
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using DF1_0.6 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/DF1_0.6
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using MDCK_0.02 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/MDCK_0.02
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using MDCK_0.07 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/MDCK_0.07
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using MDCK_0.2 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/MDCK_0.2
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## Searching for genomes in: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex
## Using MDCK_0.6 in folder: /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/filtered_gene_bc_matrices_mex/MDCK_0.6
## Loaded matrix information
## Loaded gene information
## Loaded barcode information
## Could not find summary csv:
## /Users/jacobn07/Documents/GFHK99_Multiplicity/Data/CellRanger_Output/outs/metrics_summary.csv.
## This file is only necessary if you are performing depth-normalization (calling the equalize_gbms function) in R.
## If this pipestance was produced by `cellranger aggr` with the default parameters, depth-normalization in R (via equalize_gbms) is not necessary.
## [1] 1873
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: WT ~ P3_NP + (1 | MOI)
## Data: Norm.df1 %>% filter(Cell == "DF1")
##
## REML criterion at convergence: 1803.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4141 -0.7288 -0.2562 0.7354 4.4126
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.3912 0.6255
## Residual 0.2486 0.4986
## Number of obs: 1228, groups: MOI, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.175e+00 3.132e-01 3.004e+00 3.751 0.033 *
## P3_NP 6.082e-01 3.441e-02 1.224e+03 17.677 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## P3_NP -0.026
## [1] 4.073803
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: WT ~ P3_NP + (1 | MOI)
## Data: Norm.df1 %>% filter(Cell == "MDCK")
##
## REML criterion at convergence: 593.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.2200 -0.7376 -0.1163 0.6324 3.6811
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.5677 0.7534
## Residual 0.1406 0.3750
## Number of obs: 645, groups: MOI, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.00385 0.37713 2.99782 2.662 0.0763 .
## P3_NP 0.38550 0.04631 641.02927 8.324 5.13e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## P3_NP -0.023
## [1] 2.454709
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: WT ~ P3_NP * Cell + (1 | MOI)
## Data: Norm.df1
##
## REML criterion at convergence: 2532.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4888 -0.7033 -0.2233 0.6479 4.5748
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.4129 0.6426
## Residual 0.2217 0.4709
## Number of obs: 1873, groups: MOI, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.17772 0.32169 3.00631 3.661 0.0351 *
## P3_NP 0.58077 0.03193 1866.51899 18.188 <2e-16 ***
## CellMDCK -0.22722 0.02639 1866.11271 -8.611 <2e-16 ***
## P3_NP:CellMDCK 0.01489 0.05568 1866.07896 0.267 0.7892
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) P3_NP ClMDCK
## P3_NP -0.024
## CellMDCK -0.030 0.269
## P3_NP:CMDCK 0.014 -0.474 -0.479
## [1] 3.801894
## [1] 0.4376587
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: WT ~ Cell + (1 | MOI)
## Data: Norm.df1
##
## REML criterion at convergence: 2912.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.1172 -0.6845 -0.1179 0.3882 4.2010
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.5762 0.7591
## Residual 0.2727 0.5222
## Number of obs: 1873, groups: MOI, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.31219 0.37986 3.00366 3.454 0.0407 *
## CellMDCK -0.24956 0.02565 1868.08101 -9.729 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## CellMDCK -0.024
## [1] 0.4376587
## [1] 0.7782794
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: value ~ variable + (1 | MOI)
## Data: Melt.df2
##
## REML criterion at convergence: 3050.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3174 -0.7854 0.0074 0.7636 2.5500
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.2448 0.4948
## Residual 0.2961 0.5441
## Number of obs: 1865, groups: MOI, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.185e+00 2.481e-01 3.017e+00 4.774 0.0172 *
## variableVAR 4.726e-02 2.522e-02 1.860e+03 1.874 0.0611 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## variableVAR -0.053
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Test ~ Cell * Help + (1 | MOI)
## Data: Sum.df
##
## REML criterion at convergence: 6353.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1149 -0.6928 -0.0438 0.5786 3.9675
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.6928 0.8323
## Residual 0.3017 0.5492
## Number of obs: 3845, groups: MOI, 5
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.09332 0.37266 4.00891 2.934 0.0425 *
## CellMDCK -0.25449 0.02689 3837.07352 -9.464 < 2e-16 ***
## Helpw/ mVAR2 0.39627 0.02676 3838.28675 14.810 < 2e-16 ***
## CellMDCK:Helpw/ mVAR2 0.15808 0.03673 3837.03828 4.304 1.72e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) ClMDCK H/mVAR
## CellMDCK -0.026
## Helpw/mVAR2 -0.032 0.378
## CMDCK:H/mVA 0.018 -0.729 -0.632
## [1] 0.4376587
## [1] 0.2056718
## [1] 1.490405
## [1] 2.583851
## [1] 2.818383
## [1] 3.630781
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Test ~ Cell * Help + (1 | MOI)
## Data: Sum.df %>% filter(MOI < 0.6)
##
## REML criterion at convergence: 4069.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.5909 -0.7503 -0.1978 0.6255 3.4201
##
## Random effects:
## Groups Name Variance Std.Dev.
## MOI (Intercept) 0.1748 0.4180
## Residual 0.3773 0.6142
## Number of obs: 2169, groups: MOI, 3
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.64536 0.24313 2.03858 2.654 0.115
## CellMDCK -0.41472 0.04397 2163.01633 -9.432 < 2e-16 ***
## Helpw/ mVAR2 0.17251 0.03642 2163.88745 4.737 2.31e-06 ***
## CellMDCK:Helpw/ mVAR2 0.54853 0.05587 2163.14850 9.818 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) ClMDCK H/mVAR
## CellMDCK -0.061
## Helpw/mVAR2 -0.085 0.408
## CMDCK:H/mVA 0.044 -0.788 -0.617
## Rep WT.Cells Helper.Cells
## 10 102 253
##
## Call:
## lm(formula = Pp ~ Rep, data = Exp.Pp.1 %>% mutate(Rep = Rep %>%
## factor(levels = c(1, 2, 3, 4, 5))))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25875 -0.11031 0.01063 0.08812 0.22500
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.71500 0.04533 15.775 < 2e-16 ***
## Rep2 -0.05625 0.06410 -0.878 0.38618
## Rep3 -0.05875 0.06410 -0.917 0.36565
## Rep4 -0.12250 0.06410 -1.911 0.06421 .
## Rep5 -0.24000 0.06410 -3.744 0.00065 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1282 on 35 degrees of freedom
## Multiple R-squared: 0.3186, Adjusted R-squared: 0.2407
## F-statistic: 4.091 on 4 and 35 DF, p-value: 0.007987
##
## Call:
## lm(formula = Pp ~ Rep, data = Exp.Pp.1 %>% mutate(Rep = Rep %>%
## factor(levels = c(1, 2, 3, 4))))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25875 -0.10875 0.01063 0.06906 0.20375
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.71500 0.04253 16.811 3.66e-16 ***
## Rep2 -0.05625 0.06015 -0.935 0.3577
## Rep3 -0.05875 0.06015 -0.977 0.3371
## Rep4 -0.12250 0.06015 -2.037 0.0513 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1203 on 28 degrees of freedom
## Multiple R-squared: 0.1293, Adjusted R-squared: 0.03598
## F-statistic: 1.386 on 3 and 28 DF, p-value: 0.2676
## PB2 PB1 PA HA NP NA. M NS
## 1 0.59 0.59 0.76 0.69 0.76 0.69 0.80 0.84
## 2 0.55 0.55 0.63 0.40 0.72 0.81 0.85 0.76
## 3 0.48 0.48 0.54 0.72 0.86 0.66 0.79 0.72
## 4 0.61 0.57 0.57 0.65 0.54 0.46 0.69 0.65
## Time difference of 3.565018 mins
